Stormwater Pipe Research Articles

Exploring Hydraulic Impacts of Downstream Water Levels on the Drainage Capacity of a Stormwater Pipe

Exploring Hydraulic Impacts of Downstream Water Levels on the Drainage Capacity of a Stormwater Pipe

Leveraging deep learning techniques for condition assessment of stormwater pipe network

Leveraging deep learning techniques for condition assessment of stormwater pipe network

Advancing illicit connection diagnosis of urban stormwater pipes: Comprehensive analysis with EEM fluorescence spectroscopy

Urban drainage systems are significant contributors to the issue of black-odorous water bodies. The current application of stormwater pipe inspection technologies faces substantial limitations, especially in industrial areas with diverse wastewater. This study introduced an innovative approach using excitation-emission matrix (EEM) fluorescence spectroscopy for rapid and accurate diagnosis, providing a new perspective for diagnosing illicit connections. In single wastewater-type areas like residential zones, the method achieved a remarkable 91.5 % accuracy solely through spectra observation and fluorescence peak intensity comparison, outperforming conventional NH3-N-based techniques, which reached an accuracy of only 68.1 %. For regions with complex wastewater scenarios, after EEM subtraction, the residual spectra can be roughly categorized into four distinctive categories based on characteristics. This provides a preliminary assessment and helps in initially identifying the types and sources of inflowing wastewater. Furthermore, the least squares (LS) method refines diagnosis results, offering calculated coefficients reflecting the probability and severity of suspected wastewater intrusion. Simulation experiments and field sample analyses validated the feasibility and accuracy of the EEM-based method, highlighting its advantages for diagnosing illicit connections in both single and mixed wastewater scenarios. The results can significantly narrow down the investigation scope and enhance the confirmation of wastewater sources, exhibiting promising application prospects.

Integrating the Spatial Configurations of Green and Gray Infrastructure in Urban Stormwater Networks

AbstractGreen infrastructure (GI) practices improve stormwater quality and reduce urban flooding, but as urban hydrology is highly controlled by its associated gray infrastructure (e.g., stormwater pipe network), GI's watershed‐scale performance depends on its siting within its associated watershed. Although many stormwater practitioners have begun considering GI's spatial configuration within a larger watershed, few approaches allow for flexible scenario exploration, which can untangle GI's interaction with gray infrastructure network and assess its effects on watershed hydrology. To address the gap in integrated gray‐green infrastructure planning, we used an exploratory model to examine gray‐green infrastructure performance using synthetic stormwater networks with varying degrees of flow path meandering, informed by analysis on stormwater networks from the Minneapolis‐St. Paul Metropolitan Area, MN, USA. Superimposed with different coverage and placements of GI (e.g., bioretention cells), these gray‐green stormwater networks are then subjected to different rainfall intensities within Environmental Protection Agency's Storm Water Management Model to simulate their hydrological benefits (e.g., peak flow reduction, flood reduction). Although only limited choices of green and gray infrastructure were explored, the results show that the gray infrastructure's spatial configuration can introduce tradeoffs between increased peak flow and increased flooding, and further interacts with GI coverage and placement to reduce peak flow and flooding at low rainfall intensity. However, as rainfall intensifies, GI ceases to reduce peak flow. For integrated gray‐green infrastructure planning, our results suggest that physical constraints of the stormwater networks and the range of rainfall intensities must be considered when implementing GI.

Tracking the source of antibiotic resistome in the stormwater network drainage in the presence of sewage illicit connections

Stormwater pipes are illicitly connected with sewage in many countries, which means that sewage enters stormwater pipes and the drainage is discharged to surface water without any treatment. Sewage contains more pathogens and highly risky antibiotic resistance genes (ARGs) than surface runoff. Therefore, sewage may alter the microbial and ARG compositions in stormwater pipe drainage, which in turn leads to an increased risk of resistance in surface water. However, the effects of sewage on ARGs in the drainage of stormwater networks have not been systematically studied. This study characterized the microbial and ARG composition of several environmental compartments of a typical stormwater network and quantified their contributions to those in the drainage. This network transported ARGs and microorganisms from sewage, sediments in stormwater pipes, and surface runoff into the drainage and thus into the river. According to metagenomic analysis, multidrug resistance genes were most abundant in all samples and the numbers and relative abundance of ARGs in the drainage collected during wet weather were comparable to that of sewage. The results of SourceTracker showed that the relative contribution of sewage was double that of rainwater and surface runoff in the drainage during wet weather for both microorganisms and ARGs. Desulfovibrio, Azoarcus, and Sulfuritalea were connected with the greatest number of ARGs and were most abundant in the sediments of stormwater pipes. Furthermore, stochastic processes were found to dominate ARG and microbial assembly, as the effects of high hydrodynamic intensity outweighed the effects of environmental filtration and species interactions. The findings of this study can increase our understanding of ARGs in stormwater pipe drainage, a crucial medium linking ARGs in sewage to environmental ARGs.

Carbon Accounting and Carbon Emission Reduction Potential Analysis of Sponge Cities Based on Life Cycle Assessment

In recent years, China has been vigorously carrying out the construction and development of a sponge city. To prove that the material and energy consumption involved in the implementation of a sponge city is much less than that of the integrated urban drainage system (IUDS) in addition to saved energy and reduced carbon in the sponge city, it was important to calculate the corresponding carbon source and sink and analyze its key influence factors. The emission factor method was used to calculate carbon emissions. In view of this, based on the Intergovernmental Panel on Climate Change (IPCC) guidelines and life cycle assessment (LCA), this research established a systematic accounting method for carbon emissions from the IUDS and the sponge city, which focused on improving the calculation method of the carbon sink stage. A case study was conducted in Beijing, China, and the carbon emission reduction effect of the construction of the sponge city was discussed. The results showed that the carbon emission reduction potential (CRP) of sponge facilities in this project for 50 years was 612.45 tons of CO2 equivalent after the renovation. Compared with IUDS, sponge city construction had a positive effect on carbon emission reduction and reduced carbon emissions by 87.08% on average. For the IUDS and the sponge city, the stormwater pipe network had the largest contribution of carbon emission, and its material, transportation, pipeline laying, and maintenance of stormwater pipe networks had important influences. Morris global analysis method was used to analyze the sensitivity of LCA results and obtained that the influence degree of sensitivity factors on carbon emissions in the life cycle was in the order of annual rainfall > carbon sequestration rate of green space > high-density polyethylene (HDPE) > transport distance > fertilization and insecticide. This study can provide a positive contribution to the construction of a sponge city and planning the low-carbon development of the city in the future in China.

Stormwater Infrastructure Resilience Assessment against Seismic Hazard Using Bayesian Belief Network.

Resilient stormwater infrastructure is one of the fundamental components of resilient and sustainable cities. For this, the resilience assessment of stormwater infrastructure against earthquake hazards is crucial for municipal authorities. The objective of this study is to develop a resilience assessment framework for stormwater pipe infrastructure against seismic hazards. A Bayesian belief network (BBN)-based stormwater infrastructure resilience model is constructed based on the published literature and expert knowledge. The developed framework is implemented in the city of Regina, Canada, to assess the city's stormwater pipe infrastructure resilience. The outcome of the model indicates that proposed BBN-based stormwater infrastructure resilience model can effectively quantify uncertainties and handle the nonlinear relationships between several reliability and recovery factors. The model is also capable of identifying the most sensitive and vulnerable stormwater pipes within the network.

Assessing and predicting Lake Chloride Concentrations in the Lake-Rich Urbanizing Halifax Region, Canada

Study regionHalifax, Nova Scotia, Canada. Study focusMany lakes in the Halifax region are approaching or exceeding the chronic freshwater aquatic life guideline for chloride (Cl-), presumably due to the application of deicing salts. These exceedances represent an ecological risk that requires mitigation for lakes currently experiencing high Cl-, and preventative steps should be taken to protect lakes that will be impacted by future development. In this study we paired geospatial analysis with linear regression methods to identify key factors contributing to elevated Cl- in Halifax lakes, and applied a mass balance modeling approach to estimate annual Cl- loading rates for dominant land uses within the region. New hydrological insights for the region-The watershed variables found to be most predictive of mean lake [Cl-] were the % urban coverage, road density, and stormwater pipe density in a watershed.-Annual Cl- loading rates for the four primary land use categories in the region were: rural 1–3 g/m2/yr, commercial 0–9 g/m2/yr, residential 97–162 g/m2/yr, and roads 804–964 g/m2/yr.-The mass balance model developed in this study could be used to predict Cl- loading associated with planned developments, and subsequent impacts on receiving lakes.

A follow up analysis of soil properties four years after the Dan River coal ash spill

In 2014, a storm water pipe located under a coal ash impoundment along the Dan River in North Carolina failed, releasing approximately 39,000 tons of coal ash into the river. To assess the impact of this spill on soil properties, a CURE (Course-based Undergraduate Research Experience) course was taught in 2015 and 2018. In 2015, significant differences were found in the abiotic and biotic properties of impacted soils. This study, resampling the same locations, found significant differences remain in the concentrations of phosphorous, calcium, total exchange capacity, and certain nitrogen species. Impacted sites have significantly lower microbial abundance, significantly different phylogenetic make-ups; similar, but non-significant, decreases in dehydrogenase activity; and significantly different levels of bacterial resistance to low concentrations of chromium. Given the ongoing risk of coal ash spills into North Carolina waterways, including those most recently caused by hurricanes Florence and Michael, these findings could have important implications for the potential impact of such spills upon soil microbes within similar riparian ecosystems.

Comparative performance and cost-integrated life cycle assessment of low impact development controls for sustainable stormwater management

Climate change and urbanization have led to an increase in the frequency and intensity of floods in urban regions. To cope with such extreme events, low impact development (LID) has been adopted as a sustainable alternative to conventional stormwater management systems. LID controls mitigate runoff and manage flooding at the source by providing additional storage, filtration, and infiltration of stormwater. This study aims to investigate the techno-economic and environmental performance of multiple LID controls: bioretention cells (BC), infiltration trenches (IT), and permeable interlocking concrete pavement (PICP) compared to a conventional stormwater pipe drainage system. A cost-integrated life cycle analysis was conducted to assess the environmental impacts and evaluate the financial feasibility of the examined stormwater management systems. An eco-efficiency analysis (EEA) was carried out to quantify the environmental costs of LID controls by incorporating the results of a life cycle assessment (LCA) and life cycle cost analysis (LCCA). The technical analysis showed that LID controls significantly reduced runoff by 67%, 53%, and 36% for IT, BC, and PICP, respectively compared to the conventional system. Moreover, the LCA results revealed that the pipe drainage system was the least favorable with a single score of 191 mPt, followed by PICP (188 mPt), BC (40 mPt), and IT (30 mPt). Over a 30-year assessment period, the LCCA findings indicated that the IT and BC controls had the lowest net present costs of $11.6 and $14.5 million, respectively, compared to the PICP ($17.0 million) and conventional ($19.5 million) systems. The EEA revealed that IT was the most eco-efficient (EI = 0.34 Pt/$) among the LID systems, whereas PICP was the least cost-efficient (EI = 0.97 Pt/$). It was also found that applying hybrid LID models further reduced the runoff, environmental impacts, and financial burdens by up to 79%, 84%, and 48%, respectively. Overall, these findings emphasized the potential environmental and financial benefits of implementing integrated LID controls as sustainable stormwater management systems.

Towards flood risk mapping based on multi-tiered decision making in a densely urbanized metropolitan city of Istanbul

• The AHP and ANP were performed to assess hazard and vulnerability, respectively. • DEMATEL technique was integrated to define the ANP structure for criteria assessment. • Focus group discussions were conducted at each level of the framework refinement. • Income level and education level have highest weights in vulnerability cluster. • Return period of a storm event is the most significant criteria in hazard cluster. Multi-dimensional risk assessment strategies aided by the active participation of stakeholders are essential to combat flood events for metropolitan cities. This study aims to prioritize the districts of Istanbul regarding flood hazard, flood vulnerability, and flood risk with a multi-tiered comprehensive decision-making procedure. The proposed framework was enriched by focus group discussion, which was conducted through the professionals dealing with flood risk management in Istanbul. Analytical hierarchy process (AHP) was used to evaluate hazard criteria while the vulnerability criteria were subjected to the analytical network process (ANP). The structure of the ANP was adjusted by adopting the decision-making trial and evaluation laboratory (DEMATEL) technique. VIKOR (Visekriterijumska Optimizacija I Kompromisno Resenje) method was employed to obtain district scores. Findings highlighted the income level, education level, and population density criteria regarding vulnerability cluster, while the return period of a storm event, storm water pipe network and imperviousness were the most significant hazard criteria. Sensitivity analysis of the VIKOR method also showed the robustness of the adopted methodology and the stability of the computed results under diverging conditions. The proposed generic framework can be replicated in other densely urbanized metropolitan cities and corresponding recommendations could assist decision-makers in achieving sustainable development goals.

Concentrations and risk assessment of metals and microplastics from antifouling paint particles in the coastal sediment of a marina in Simon's Town, South Africa.

Maintenance of maritime vessels includes the removal of paint from hulls that are sources of metals, antifouling paint particles (APPs) and microplastics (MPs) that end up in the coastal environment. Simon's Town is a small urban town in False Bay, Cape Town, South Africa, where maritime activities take place (there is a naval harbour, marina and shipyard). The aim of this study was to measure metals, APPs and MPs in Simon's Town, to assess the impact of maritime activities and a storm water pipe in a sheltered marina. Sediment samples were collected from six sites during winter 2018. Sediment and extracted APPs were analysed for metal concentrations (Al, As, B, Ba, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Se, Sb, Sn, Sr, V and Zn) and MPs characterised based on type (shape and polymer), colour and size. Highest average metal concentrations in sediment for all sites were Fe (32228 ± SEM 4024), Al (12271 ± 1062) and Cu (1129 ± 407). Metals in paint particles were highest for Fe (80873 ± 19341), Cu (66762 ± 13082) and Zn (44910 ± 1400µg/g). Metal and MP fragment concentrations were highest at the slipway of the shipyard, decreasing with increased distance from the slipway. MP filaments were highest close to the storm water outfall pipe. Our results suggest that shipyards are potential sources of metals and MP fragments (mainly APPs), with storm water pipes potential sources of MP filaments. Various indices applied to assess the potential impacts of metals and MPs suggest that these contaminants have the potential to adversely impact the intertidal ecosystem investigated.

Earthquake Resilience Framework for a Stormwater Pipe Infrastructure System Integrating the Best Worst Method and Dempster–Shafer Theory

Stormwater pipe infrastructure is a fundamental requirement of any nation, but pipes can be damaged in natural disasters. Consequently, evaluating the resilience of stormwater infrastructure to earthquake damage is an essential duty for any city because it outlines the capability to recover from a disaster after the event. The resilience quantification process needs various data types from various sources, and uncertainty and partial data may be included. This study recommends a resilience assessment framework for stormwater pipe infrastructure facing earthquake hazards using Hierarchical Evidential Reasoning (HER) on the basis of the Dempster–Shafer (D-S) theory. The developed framework was implemented in the City of Regina, SK, Canada to quantify the resilience of the stormwater pipe infrastructure. First, various resilience factors were identified from the literature. Based on experts’ judgment, the weight of these factors was determined using the Best Worst Method (BWM). After that, the resilience was determined using the D–S theory. Finally, sensitivity analysis was conducted to examine the sensitivity of the factors of the recommended hierarchical stormwater infrastructure resilience model. The recommended earthquake resilience assessment model produced satisfying outcomes, which showed the condition state of resilience with the degree of uncertainty.

A Safety Factor Approach to Designing Urban Infrastructure for Dynamic Conditions

AbstractCurrent approaches to design flood‐sensitive infrastructure typically assume a stationary rainfall distribution and neglect many uncertainties. These assumptions are inconsistent with observations that suggest intensifying extreme precipitation events and the uncertainties surrounding projections of the coupled natural‐human systems. Here we demonstrate a safety factor approach to designing urban infrastructure in a changing climate. Our results show that assuming climate stationarity and neglecting deep uncertainties can drastically underestimate flood risks and lead to poor infrastructure design choices. We find that climate uncertainty dominates the socioeconomic and engineering uncertainties that impact the hydraulic reliability in stormwater drainage systems. We quantify the upfront costs needed to achieve higher hydraulic reliability and robustness against the deep uncertainties surrounding projections of rainfall, surface runoff characteristics, and infrastructure lifetime. Depending on the location, we find that adding safety factors of 1.4–1.7 to the standard stormwater pipe design guidance produces robust performance to the considered deep uncertainties. The insights gained from this study highlights the need for updating traditional engineering design strategies to improve infrastructure reliability under socioeconomic and environmental changes.

Impacts of Extreme Hydrological Events on the Behavior of Buried Stormwater Pipe

AbstractThis study focused on estimating the strength and deformation behavior of buried concrete pipe subjected to heavy rainfall-induced flooding, soil infiltration, leaks from the buried pipe, a...

Riparian Land Cover, Water Temperature Variability, and Thermal Stress for Aquatic Species in Urban Streams

Thermal regime warming and increased variability can result in human developed watersheds due to runoff over impervious surfaces and influence of stormwater pipes. This study quantified relationships between tree canopy, impervious surface, and water temperature in stream sites with 4 to 62% impervious land cover in their “loggersheds” to predict water temperature metrics relevant to aquatic species thermal stress thresholds. This study identified significant (≥0.7, p < 0.05) negative correlations between water temperature and percent tree canopy in the 5 m riparian area and positive correlations between water temperature and total length of stormwater pipe in the loggershed. Mixed-effects models predicted that tree canopy cover in the 5 m riparian area would reduce water temperatures 0.01 to 6 °C and total length of stormwater pipes in the loggershed would increase water temperatures 0.01 to 2.6 °C. To our knowledge, this is the first time that the relationship between stormwater pipes and water temperature metrics has been explored to better understand thermal dynamics in urban watersheds. The results highlight important aspects of thermal habitat quality and water temperature variability for aquatic species living in urban streams based on thermal thresholds relevant to species metabolism, growth, and life history.

Assessment on the Effectiveness of Urban Stormwater Management

Stormwater management is a key issue in line with global problems of urbanization and climate change. Assessing the effectiveness in managing stormwater is crucial to maintain urban resilience to flooding risk. A method based on a stormwater management model (SWMM) was developed for assessing the control of stormwater runoff volume and the percentage removal of suspended solids by implementing a Sponge City strategy. An interdisciplinary approach was adopted incorporating Low Impact Development (LID) with urban green infrastructure and grey infrastructure paradigms in a typical old residential community in Suzhou, China. Sponge facilities for reducing stormwater runoff included bio-retention cells, permeable pavements, grassed pitches, and stormwater gardens. The simulation results of SWMM show that the stormwater pipe system can meet the management standard for storms with a five-year recurrence interval. The volume capture ratio of annual runoff was 91%, which is higher than control target of 80%. The suspended solids reduction rate was 56%, which meets the requirement of planning indicators. Thus, the proposed method of spongy facilities can be used for renovation planning in old residential areas in China. Implementing spongy facilities with a LID strategy for stormwater management can significantly enhance urban water resilience and improve ecosystem services.

The abundance and characteristics of microplastics in rainwater pipelines in Wuhan, China

Urban rainwater runoff is considered to be an important way to transport microplastics into the freshwater. By analyzing the microplastics in rainwater pipelines in different land function areas in Hongshan District (Wuhan, China), the preliminary results of microplastics abundance and characteristics in rainwater pipelines and rainwater pipeline sediments were obtained. The microplastics abundance in water samples was 2.75 ± 0.76 to 19.04 ± 2.96 items/L, the abundance of microplastics in the sediment was 6.00 ± 1.63 to 27.33 ± 4.64 items/100 g. The highest abundance among the samples was in the business district and the lowest in the campus. The microplastics in water samples and sediment samples were mainly fragments, accounting for 44.7% and 57.1%, respectively. The proportion of particle size <1 mm was 75.0% and above. The color of microplastics was diversified, and colored particles occupied over 60.0%. The types of polymers detected were mainly polyethylene, polypropylene and polyester, which were related to the types of polymers widely used in life. This study shows that urban rainwater pipelines is one of the ways for land-based microplastics to migrate to freshwater, and the accumulation of microplastics in stormwater pipe sediments might be an important contributor to microplastics in freshwater area.

A Nonparametric Stochastic Approach for Disaggregation of Daily to Hourly Rainfall Using 3-Day Rainfall Patterns

As infrastructure and populations are highly condensed in megacities, urban flood management has become a significant issue because of the potentially severe loss of lives and properties. In the megacities, rainfall from the catchment must be discharged throughout the stormwater pipe networks of which the travel time is less than one hour because of the high impervious rate. For a more accurate calculation of runoff from the urban catchment, hourly or even sub-hourly (minute) rainfall data must be applied. However, the available data often fail to meet the hydrologic system requirements. Many studies have been conducted to disaggregate time-series data while preserving distributional statistics from observed data. The K-nearest neighbor resampling (KNNR) method is a useful application of the nonparametric disaggregation technique. However, it is not easy to apply in the disaggregation of daily rainfall data into hourly while preserving statistical properties and boundary continuity. Therefore, in this study, three-day rainfall patterns were proposed to improve reproducible ability of statistics. Disaggregated rainfall was resampled only from a group having the same three-day rainfall patterns. To show the applicability of the proposed disaggregation method, probability distribution and L-moment statistics were compared. The proposed KNNR method with three-day rainfall patterns reproduced better the characteristics of rainfall event such as event duration, inter-event time, and toral amount of rainfall event. To calculate runoff from urban catchment, rainfall event is more important than hourly rainfall depth itself. Therefore, the proposed stochastic disaggregation method is useful to hydrologic analysis, particularly in rainfall disaggregation.

Matching analysis of investment structure and urban inundation control function of sponge cities in China

The risk of urban flood inundation has been increasing worldwide. To address this problem, the sponge city strategy has been proposed in China. This study focuses on the issue of urban flood inundation, which is a main problem that the construction of sponge cities seeks to address. The design mode of sponge city flood control and drainage systems (SCFCDSs) is examined, including source control systems (SCSs), stormwater pipe network systems (SPNSs), and over-standard stormwater storage and drainage systems (OSSSDSs). A quantitative method to evaluate flood control and drainage capacity (stormwater equivalent) of SCFCDSs is proposed and applied to quantitatively analyze the matching relationship between investment structure and inundation control function. Based on 18 pilot cities, the stormwater equivalents of the SCSs, SPNSs, and OSSSDSs account for 13.8, 57.7, and 28.6% of the stormwater equivalent of SCFCDSs on average, respectively. On the other hand, the investments in SCSs, SPNSs, and OSSSDSs account for 66.1, 15.0, and 18.9% of the total investment in SCFCDSs on average, respectively. The results show that an unbalanced investment structure and corresponding design standards along with insufficient investment in OSSSDSs are the key factors hindering the effective implementation of urban flood inundation control in sponge cities.